Despite the advancement of science and technology, humans are still required to achieve complex tasks in which small errors may be very costly. Errors may occur for instance due to fatigue/drowsiness. In the case of a moving vessel such as a truck, the outcome of such errors may be tragic.
It is known to detect drowsiness using various methods. For instance, in the PERCLOS (PERcent eyelid CLOSure) method, a measure of the percentage of eyelid closure over the pupil over time is performed and reflects slow eyelid closures rather than blinks. Unfortunately, such detecting is often of limited interest since, at this point, it is too late to implement an alternative strategy and the situation may already be critical. There is therefore a need for a method and apparatus which enable a prediction of drowsiness.
In another prior art method an EEG (Electroencephalogram) is used to measure signal components over 30 Hz which are known to have a correlation with a subject's drowsiness. Unfortunately such method is cumbersome.
There is a need for a method and apparatus that will overcome at least one of the above-identified drawbacks.